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The distributions of the $m$-th longest runs of multivariate random sequences are considered. For random sequences made up of $k$ kinds of letters, the lengths of the runs are sorted in two ways to give two definitions of run length…

Combinatorics · Mathematics 2024-05-06 Yong Kong

We consider a class of generalized binomials emerging in fractional calculus. After establishing some general properties, we focus on a particular yet relevant case, for which we provide several ready-for-use combinatorial identities,…

Combinatorics · Mathematics 2020-10-13 Mirko D'Ovidio , Anna Chiara Lai , Paola Loreti

In the present article the author extends the Fourier transform to a more general class of functions; First to power-law functions with integer and half-integer exponents then to the widely used quantum statistics function (Fermi-Dirac and…

General Mathematics · Mathematics 2019-12-30 Cyril Belardinelli

In this article, we study a notion of the extraction rate of Turing functionals that translate between notions of randomness with respect to different underlying probability measures. We analyze several classes of extraction procedures: a…

Logic · Mathematics 2021-03-09 Douglas Cenzer , Christopher P. Porter

A theoretical framework is developed to describe the transformation that distributes probability density functions uniformly over space. In one dimension, the cumulative distribution can be used, but does not generalize to higher…

Neural and Evolutionary Computing · Computer Science 2016-09-08 Eric Kee

Recently, the weight distributions of the duals of the cyclic codes with two zeros have been obtained for several cases. In this paper we provide a slightly different approach toward the general problem and use it to solve one more special…

Number Theory · Mathematics 2011-11-15 Maosheng Xiong

There is an increasing interest in algorithms to learn invariant correlations across training environments. A big share of the current proposals find theoretical support in the causality literature but, how useful are they in practice? The…

Machine Learning · Computer Science 2021-02-23 Benjamin Aubin , Agnieszka Słowik , Martin Arjovsky , Leon Bottou , David Lopez-Paz

In this work, we revisit the problem of uniformity testing of discrete probability distributions. A fundamental problem in distribution testing, testing uniformity over a known domain has been addressed over a significant line of works, and…

Data Structures and Algorithms · Computer Science 2017-08-17 Tuğkan Batu , Clément L. Canonne

Quantum walks can reconstruct quantum algorithms for quantum computation, where the precise controls of quantum state transfers between arbitrary distant sites are required. Here, we investigate quantum walks using a periodically…

Quantum Physics · Physics 2020-04-06 Haruna Katayama , Noriyuki Hatakenaka , Toshiyuki Fujii

Windowed recurrences are sliding window calculations where a function is applied iteratively across the window of data, and are ubiquitous throughout the natural, social, and computational sciences. In this monograph we explore the…

Data Structures and Algorithms · Computer Science 2026-02-13 David K. Maslen , Daniel N. Rockmore

Faced with a sequence of N binary events, such as coin flips (or Ising spins), it is natural to ask whether these events reflect some underlying dynamic signals or are just random. Plausible models for the dynamics of hidden biases lead to…

Neurons and Cognition · Quantitative Biology 2007-05-23 William Bialek

Quantum walks, the quantum mechanical counterpart of classical random walks, is an advanced tool for building quantum algorithms that has been recently shown to constitute a universal model of quantum computation. Quantum walks is now a…

Quantum Physics · Physics 2012-10-01 Salvador E. Venegas-Andraca

Continuous time random walks are non-Markovian stochastic processes, which are only partly characterized by single-time probability distributions. We derive a closed evolution equation for joint two-point probability density functions of a…

Statistical Mechanics · Physics 2009-11-13 A. Baule , R. Friedrich

We present explicit formulae for parameterized families of probabilities of the number of nonoverlapping words and increasing nonoverlapping words in independent and identically distributed (i.i.d.) finite valued random variables,…

Probability · Mathematics 2025-12-18 Hayato Takahashi

This paper offers a mathematical invention that shows how to convert integrated quantiles, which often appear in risk measures, into integrated cumulative distribution functions, which are technically more tractable from various…

Risk Management · Quantitative Finance 2023-04-26 Yunran Wei , Ricardas Zitikis

In this paper the generalization of the Poisson distribution is derived for the case when each consecutive event changes event rate. A simple formula for the probability of observing of a given number of events for the selected period of…

Data Analysis, Statistics and Probability · Physics 2014-01-06 E. A. Kushnirenko

Let F be a distribution function with negative mean and regularly varying right tail. Under a mild smoothness condition we derive higher order asymptotic expansions for the tail distribution of the maxima of the random walk generated by F.…

Probability · Mathematics 2007-05-23 Ph . Barbe , W. P. McCormick , C. Zhang

Quantum walk (QW) is the quantum analog of the random walk. QW is an integral part of the development of numerous quantum algorithms. Hence, an in-depth understanding of QW helps us to grasp the quantum algorithms. We revisit the…

Quantum Physics · Physics 2021-02-16 Mahesh N. Jayakody , Chandrakala Meena , Priodyuti Pradhan

We introduce the space of grid functions, a space of generalized functions of nonstandard analysis that provides a coherent generalization both of the space of distributions and of the space of Young measures. We will show that in the space…

Functional Analysis · Mathematics 2019-07-15 Emanuele Bottazzi

Despite recent successes of large pre-trained language models in solving reasoning tasks, their inference capabilities remain opaque. We posit that such models can be made more interpretable by explicitly generating interim inference rules,…

Computation and Language · Computer Science 2021-06-07 Debjit Paul , Anette Frank